AI Masters ML Engineering Intern

What you'll do

• Build and ship features for the Research AIOS platform within assigned domains like Data, Compute, or Model.
• Write production-quality code that follows established team architectural standards and design patterns.
• Design, implement, and test platform capabilities to support large-scale AI systems in a regulated environment.
• Participate in code reviews, design discussions, and standard agile sprint ceremonies.
• Develop technical depth in ML systems engineering including agent orchestration, model serving, and data pipelines.
• Document technical work and share key learnings with the broader engineering team.
• Present final project outcomes and results to team members and leadership at the end of the rotation.

What we're looking for

• Currently pursuing a Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• Completion of at least 2 years of undergraduate program or currently enrolled in a graduate program.
• Coursework or project experience in machine learning, distributed systems, data engineering, or software systems design.
• Familiarity with at least one cloud platform (AWS, GCP, Azure) or containerization (Docker, Kubernetes).
• Authorized to work in the United States on a full-time basis.
• Foundational programming skills in Python, Go, or TypeScript.
• Exposure to machine learning concepts through coursework, personal projects, or research.
• Prior experience using AI tools in an academic, project, or work setting (preferred).